renaissance-movie-lens_0
[2025-02-20T21:55:37.266Z] Running test renaissance-movie-lens_0 ...
[2025-02-20T21:55:37.266Z] ===============================================
[2025-02-20T21:55:37.266Z] renaissance-movie-lens_0 Start Time: Thu Feb 20 21:55:35 2025 Epoch Time (ms): 1740088535211
[2025-02-20T21:55:37.266Z] variation: NoOptions
[2025-02-20T21:55:37.266Z] JVM_OPTIONS:
[2025-02-20T21:55:37.266Z] { \
[2025-02-20T21:55:37.266Z] echo ""; echo "TEST SETUP:"; \
[2025-02-20T21:55:37.266Z] echo "Nothing to be done for setup."; \
[2025-02-20T21:55:37.266Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400848694977/renaissance-movie-lens_0"; \
[2025-02-20T21:55:37.266Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400848694977/renaissance-movie-lens_0"; \
[2025-02-20T21:55:37.266Z] echo ""; echo "TESTING:"; \
[2025-02-20T21:55:37.266Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400848694977/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-20T21:55:37.266Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400848694977/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-20T21:55:37.266Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-20T21:55:37.266Z] echo "Nothing to be done for teardown."; \
[2025-02-20T21:55:37.266Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400848694977/TestTargetResult";
[2025-02-20T21:55:37.266Z]
[2025-02-20T21:55:37.266Z] TEST SETUP:
[2025-02-20T21:55:37.266Z] Nothing to be done for setup.
[2025-02-20T21:55:37.266Z]
[2025-02-20T21:55:37.266Z] TESTING:
[2025-02-20T21:55:50.744Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-20T21:56:04.249Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-02-20T21:56:29.854Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-20T21:56:29.854Z] Training: 60056, validation: 20285, test: 19854
[2025-02-20T21:56:29.854Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-20T21:56:29.854Z] GC before operation: completed in 353.769 ms, heap usage 102.741 MB -> 36.483 MB.
[2025-02-20T21:57:13.452Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T21:57:35.459Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T21:57:54.419Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T21:58:13.370Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T21:58:24.968Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T21:58:35.313Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T21:58:45.061Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T21:58:54.871Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T21:58:56.470Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T21:58:59.897Z] The best model improves the baseline by 14.52%.
[2025-02-20T21:59:00.638Z] Movies recommended for you:
[2025-02-20T21:59:00.638Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T21:59:00.638Z] There is no way to check that no silent failure occurred.
[2025-02-20T21:59:00.638Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (150538.980 ms) ======
[2025-02-20T21:59:00.638Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-20T21:59:01.409Z] GC before operation: completed in 419.795 ms, heap usage 161.409 MB -> 46.773 MB.
[2025-02-20T21:59:17.237Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T21:59:30.771Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T21:59:47.002Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:00:03.671Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:00:13.579Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:00:21.818Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:00:31.572Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:00:41.589Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:00:42.349Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:00:42.349Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:00:43.094Z] Movies recommended for you:
[2025-02-20T22:00:43.094Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:00:43.094Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:00:43.094Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (101728.014 ms) ======
[2025-02-20T22:00:43.094Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-20T22:00:43.094Z] GC before operation: completed in 480.482 ms, heap usage 184.921 MB -> 49.069 MB.
[2025-02-20T22:00:57.066Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:01:16.386Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:01:33.281Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:01:47.640Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:01:54.838Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:02:05.251Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:02:16.034Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:02:23.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:02:24.799Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:02:24.799Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:02:24.799Z] Movies recommended for you:
[2025-02-20T22:02:24.799Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:02:24.799Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:02:24.800Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (101901.907 ms) ======
[2025-02-20T22:02:24.800Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-20T22:02:25.638Z] GC before operation: completed in 627.825 ms, heap usage 134.305 MB -> 49.232 MB.
[2025-02-20T22:02:39.814Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:02:56.373Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:03:14.952Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:03:32.189Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:03:39.428Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:03:49.813Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:04:00.099Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:04:08.809Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:04:09.637Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:04:09.637Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:04:09.637Z] Movies recommended for you:
[2025-02-20T22:04:09.637Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:04:09.637Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:04:09.637Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (104207.891 ms) ======
[2025-02-20T22:04:09.637Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-20T22:04:10.448Z] GC before operation: completed in 621.405 ms, heap usage 62.401 MB -> 50.194 MB.
[2025-02-20T22:04:24.751Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:04:39.998Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:04:56.671Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:05:14.862Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:05:27.179Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:05:38.827Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:05:48.694Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:05:59.186Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:05:59.966Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:05:59.966Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:06:00.751Z] Movies recommended for you:
[2025-02-20T22:06:00.751Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:06:00.751Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:06:00.751Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (110113.165 ms) ======
[2025-02-20T22:06:00.751Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-20T22:06:01.524Z] GC before operation: completed in 745.511 ms, heap usage 125.026 MB -> 51.928 MB.
[2025-02-20T22:06:18.615Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:06:32.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:06:49.432Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:07:01.571Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:07:09.526Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:07:20.269Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:07:28.959Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:07:35.998Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:07:36.797Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:07:36.797Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:07:37.621Z] Movies recommended for you:
[2025-02-20T22:07:37.621Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:07:37.621Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:07:37.621Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (96121.865 ms) ======
[2025-02-20T22:07:37.621Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-20T22:07:38.446Z] GC before operation: completed in 610.437 ms, heap usage 82.076 MB -> 49.655 MB.
[2025-02-20T22:07:52.571Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:08:04.665Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:08:19.347Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:08:31.469Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:08:38.634Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:08:44.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:08:51.531Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:09:00.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:09:01.001Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:09:01.001Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:09:01.001Z] Movies recommended for you:
[2025-02-20T22:09:01.001Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:09:01.001Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:09:01.001Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (83032.996 ms) ======
[2025-02-20T22:09:01.001Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-20T22:09:01.814Z] GC before operation: completed in 498.079 ms, heap usage 60.862 MB -> 49.800 MB.
[2025-02-20T22:09:16.025Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:09:25.354Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:09:37.424Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:09:47.976Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:09:55.154Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:10:01.000Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:10:09.650Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:10:16.793Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:10:17.585Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:10:18.377Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:10:18.377Z] Movies recommended for you:
[2025-02-20T22:10:18.377Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:10:18.377Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:10:18.377Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (76691.169 ms) ======
[2025-02-20T22:10:18.377Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-20T22:10:19.171Z] GC before operation: completed in 428.773 ms, heap usage 168.225 MB -> 50.173 MB.
[2025-02-20T22:10:33.937Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:10:43.870Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:10:57.747Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:11:07.457Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:11:14.259Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:11:18.629Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:11:26.970Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:11:35.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:11:35.253Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:11:36.021Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:11:36.021Z] Movies recommended for you:
[2025-02-20T22:11:36.021Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:11:36.021Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:11:36.021Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (77112.184 ms) ======
[2025-02-20T22:11:36.021Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-20T22:11:36.801Z] GC before operation: completed in 425.229 ms, heap usage 202.798 MB -> 50.051 MB.
[2025-02-20T22:11:46.774Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:11:58.601Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:12:08.379Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:12:18.294Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:12:22.744Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:12:28.341Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:12:36.709Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:12:41.814Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:12:41.814Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:12:41.814Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:12:42.578Z] Movies recommended for you:
[2025-02-20T22:12:42.578Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:12:42.578Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:12:42.579Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (66104.555 ms) ======
[2025-02-20T22:12:42.579Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-20T22:12:42.579Z] GC before operation: completed in 358.085 ms, heap usage 250.577 MB -> 50.193 MB.
[2025-02-20T22:12:52.476Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:13:02.267Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:13:16.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:13:24.298Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:13:31.147Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:13:37.961Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:13:45.361Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:13:49.780Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:13:51.385Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:13:51.385Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:13:51.385Z] Movies recommended for you:
[2025-02-20T22:13:51.385Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:13:51.385Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:13:51.385Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (68695.004 ms) ======
[2025-02-20T22:13:51.385Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-20T22:13:52.142Z] GC before operation: completed in 313.224 ms, heap usage 81.246 MB -> 49.833 MB.
[2025-02-20T22:14:01.981Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:14:13.693Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:14:27.460Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:14:41.886Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:14:48.772Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:14:55.709Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:15:04.121Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:15:12.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:15:13.265Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:15:13.265Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:15:14.057Z] Movies recommended for you:
[2025-02-20T22:15:14.057Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:15:14.057Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:15:14.057Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (81978.944 ms) ======
[2025-02-20T22:15:14.057Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-20T22:15:14.057Z] GC before operation: completed in 521.690 ms, heap usage 180.111 MB -> 50.193 MB.
[2025-02-20T22:15:30.414Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:15:42.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:15:59.151Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:16:10.805Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:16:17.705Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:16:24.626Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:16:34.621Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:16:42.938Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:16:43.716Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:16:43.716Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:16:43.716Z] Movies recommended for you:
[2025-02-20T22:16:43.716Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:16:43.716Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:16:43.716Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (89591.043 ms) ======
[2025-02-20T22:16:43.716Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-20T22:16:44.482Z] GC before operation: completed in 513.828 ms, heap usage 74.542 MB -> 50.043 MB.
[2025-02-20T22:16:56.634Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:17:06.479Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:17:18.163Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:17:30.708Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:17:37.545Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:17:41.983Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:17:46.431Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:17:49.834Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:17:50.606Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:17:51.387Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:17:51.388Z] Movies recommended for you:
[2025-02-20T22:17:51.388Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:17:51.388Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:17:51.388Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (66854.753 ms) ======
[2025-02-20T22:17:51.388Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-20T22:17:52.231Z] GC before operation: completed in 513.359 ms, heap usage 157.774 MB -> 49.910 MB.
[2025-02-20T22:18:04.482Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:18:11.320Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:18:23.034Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:18:29.982Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:18:35.549Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:18:41.168Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:18:51.004Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:18:54.137Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:18:54.938Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:18:54.938Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:18:54.938Z] Movies recommended for you:
[2025-02-20T22:18:54.938Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:18:54.938Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:18:54.938Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (63316.694 ms) ======
[2025-02-20T22:18:54.938Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-20T22:18:55.725Z] GC before operation: completed in 521.629 ms, heap usage 140.404 MB -> 50.050 MB.
[2025-02-20T22:19:09.741Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:19:21.319Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:19:33.158Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:19:47.059Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:19:52.639Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:19:59.494Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:20:06.982Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:20:12.587Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:20:13.380Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:20:13.380Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:20:13.380Z] Movies recommended for you:
[2025-02-20T22:20:13.380Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:20:13.380Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:20:13.380Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (77961.332 ms) ======
[2025-02-20T22:20:13.380Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-20T22:20:14.169Z] GC before operation: completed in 341.608 ms, heap usage 192.038 MB -> 49.654 MB.
[2025-02-20T22:20:24.024Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:20:35.647Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:20:47.296Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:20:57.111Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:21:02.702Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:21:08.273Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:21:14.367Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:21:19.924Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:21:19.924Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:21:20.733Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:21:20.733Z] Movies recommended for you:
[2025-02-20T22:21:20.733Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:21:20.733Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:21:20.733Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (66696.692 ms) ======
[2025-02-20T22:21:20.733Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-20T22:21:21.504Z] GC before operation: completed in 486.805 ms, heap usage 91.094 MB -> 48.151 MB.
[2025-02-20T22:21:31.454Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:21:43.205Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:21:54.863Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:22:06.477Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:22:13.330Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:22:20.677Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:22:26.325Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:22:33.322Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:22:33.322Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:22:34.077Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:22:34.077Z] Movies recommended for you:
[2025-02-20T22:22:34.077Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:22:34.077Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:22:34.077Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (72824.880 ms) ======
[2025-02-20T22:22:34.077Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-20T22:22:34.866Z] GC before operation: completed in 447.548 ms, heap usage 204.725 MB -> 49.102 MB.
[2025-02-20T22:22:44.765Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:22:56.485Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:23:08.165Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:23:18.000Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:23:25.338Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:23:30.867Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:23:39.081Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:23:46.090Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:23:46.852Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:23:46.852Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:23:47.598Z] Movies recommended for you:
[2025-02-20T22:23:47.598Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:23:47.599Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:23:47.599Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (73040.559 ms) ======
[2025-02-20T22:23:47.599Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-20T22:23:48.369Z] GC before operation: completed in 480.098 ms, heap usage 190.828 MB -> 48.318 MB.
[2025-02-20T22:23:58.164Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T22:24:08.537Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T22:24:16.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T22:24:26.668Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T22:24:32.263Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T22:24:37.885Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T22:24:44.857Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T22:24:50.459Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T22:24:52.051Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-20T22:24:52.051Z] The best model improves the baseline by 14.52%.
[2025-02-20T22:24:52.051Z] Movies recommended for you:
[2025-02-20T22:24:52.051Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T22:24:52.051Z] There is no way to check that no silent failure occurred.
[2025-02-20T22:24:52.051Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (64131.062 ms) ======
[2025-02-20T22:24:54.531Z] -----------------------------------
[2025-02-20T22:24:54.531Z] renaissance-movie-lens_0_PASSED
[2025-02-20T22:24:54.531Z] -----------------------------------
[2025-02-20T22:24:54.531Z]
[2025-02-20T22:24:54.531Z] TEST TEARDOWN:
[2025-02-20T22:24:54.531Z] Nothing to be done for teardown.
[2025-02-20T22:24:54.531Z] renaissance-movie-lens_0 Finish Time: Thu Feb 20 22:24:53 2025 Epoch Time (ms): 1740090293912